class_docstr: An LSTM wrapper serving as an interface for ModelV2s that set use_lstm.
code: def value_function(self) -> TensorType:
      assert self._features is not None, "must call forward() first"
      return torch.reshape(self._value_branch(self._features), [-1])
  
imports: import numpy
  import gymnasium
  from gymnasium.spaces import Discrete, MultiDiscrete
  import tree
  from typing import Dict, List, Union, Tuple
  from ray.rllib.models.modelv2 import ModelV2
  from ray.rllib.models.torch.misc import SlimFC
  from ray.rllib.models.torch.torch_modelv2 import TorchModelV2
  from ray.rllib.policy.rnn_sequencing import add_time_dimension
  from ray.rllib.policy.sample_batch import SampleBatch
  from ray.rllib.policy.view_requirement import ViewRequirement
  from ray.rllib.utils.annotations import override, DeveloperAPI
  from ray.rllib.utils.framework import try_import_torch
  from ray.rllib.utils.spaces.space_utils import get_base_struct_from_space
  from ray.rllib.utils.torch_utils import flatten_inputs_to_1d_tensor, one_hot
  from ray.rllib.utils.typing import ModelConfigDict, TensorType
  from ray.rllib.utils.deprecation import deprecation_warning
  from ray.util.debug import log_once
label_desc: Use image node_id 5 for calling the LSTMWrapper obj's underlying member method code with example usage: obj.value_function() and returns: torch